The present invention relates to transmission of data in a network environment. More specifically, the present invention relates to methods and apparatus for improving the efficiency with which data are transmitted over the Internet. Still more specifically, the present invention provides techniques by which the efficiency of an Internet cache may be improved.
Generally speaking, when a client platform communicates with some remote server, whether via the Internet or an intranet, it crafts a data packet which defines a TCP connection between the two hosts, i.e., the client platform and the destination server. More specifically, the data packet has headers which include the destination IP address, the destination port, the source IP address, the source port, and the protocol type. The destination IP address might be the address of a well known World Wide Web (WWW) search engine such as, for example, Yahoo, in which case, the protocol would be TCP and the destination port would be port 80, a well known port for http and the WWW. The source IP address would, of course, be the IP address for the client platform and the source port would be one of the TCP ports selected by the client. These five pieces of information define the TCP connection.
Given the increase of traffic on the World Wide Web and the growing bandwidth demands of ever more sophisticated multimedia content, there has been constant pressure to find more efficient ways to service data requests than opening direct TCP connections between a requesting client and the primary repository for the desired data. Interestingly, one technique for increasing the efficiency with which data requests are serviced came about as the result of the development of network firewalls in response to security concerns. In the early development of such security measures, proxy servers were employed as firewalls to protect networks and their client machines from corruption by undesirable content and unauthorized access from the outside world. Proxy servers were originally based on Unix machines because that was the prevalent technology at the time. This model was generalized with the advent of SOCKS which was essentially a daemon on a Unix machine. Software on a client platform on the network protected by the firewall was specially configured to communicate with the resident demon which then made the connection to a destination platform at the client's request. The demon then passed information back and forth between the client and destination platforms acting as an intermediary or “proxy.”
Not only did this model provide the desired protection for the client's network, it gave the entire network the IP address of the proxy server, therefore simplifying the problem of addressing of data packets to an increasing number of users. Moreover, because of the storage capability of the proxy server, information retrieved from remote servers could be stored rather than simply passed through to the requesting platform. This storage capability was quickly recognized as a means by which access to the World Wide Web could be accelerated. That is, by storing frequently requested data, subsequent requests for the same data could be serviced without having to retrieve the requested data from its original remote source. Currently, most Internet service providers (ISPs) accelerate access to their web sites using proxy servers.
Unfortunately, interaction with such proxy servers is not transparent, requiring each end user to select the appropriate proxy configuration in his or her browser to allow the browser to communicate with the proxy server. For the large ISPs with millions of customers there is significant overhead associated with handling tech support calls from customers who have no idea what a proxy configuration is. Additional overhead is associated with the fact that different proxy configurations must be provided for different customer operating systems. The considerable economic expense represented by this overhead offsets the benefits derived from providing accelerated access to the World Wide Web. Another problem arises as the number of WWW users increases. That is, as the number of customers for each ISP increases, the number of proxy servers required to service the growing customer base also increases. This, in turn, presents the problem of allocating packet traffic among multiple proxy servers.
Another technique for increasing the efficiency with which data requests are serviced is described in commonly assigned, copending U.S. patent application Ser. No. 08/946,867 for METHOD AND APPARATUS FOR FACILITATING NETWORK DATA TRANSMISSIONS filed Oct. 8, 1997, the entirety of which is incorporated herein by reference for all purposes. The invention described in that copending application represents an improvement over the proxy server model which is transparent to end users, high performance, and fault tolerant. By altering the operating system code of an existing router, the router is enabled to redirect data traffic of a particular protocol intended for a specified port, e.g., TCP with port 80, to one or more caching engines connected to the router via an interface having sufficient bandwidth such as, for example, a 100baseT interface. If there are multiple caching engines connected to the cache-enabled router, the router selects from among the available caching engines for a particular request based on a simple algorithm according to which a particular group of addresses is associated with each caching engine.
The caching engine to which the request is re-routed “spoofs” the requested destination platform and accepts the request on its behalf via a standard TCP connection established by the cache-enable router. If the requested information is already stored in the caching engine, i.e., a cache “hit” occurs, it is transmitted to the requesting platform with a header indicating its source as the destination platform. If the requested information is not in the caching engine, i.e., a cache “miss” occurs, the caching engine opens a direct TCP connection with the destination platform, downloads the information, stores it for future use, and transmits it to the requesting platform. All of this is transparent to the user at the requesting platform which operates exactly as if it were communicating with the destination platform. Thus, the need for configuring the requesting platform to suit a particular proxy configuration is eliminated along with the associated overhead. Moreover, traffic may be easily allocated among as many caching engines as become necessary. Thus, content caching provides a way to compensate for the bandwidth limitations discussed above.
The success of content caching in compensating for bandwidth limitations corresponds directly to the efficiency with which the caching engines operate. The higher the cache hit rate, i.e., cache hits as a percentage of the total number of requests, the greater the bandwidth savings. For a typical caching engine, the cache hit rate is approximately 30 to 40%. This percentage includes cache misses for non-cacheable objects. This means that 60 to 70% of objects stored in caching engines are never used again. That is, 60 to 70% of the caching engine's storage is used to store objects which will never be requested again. In addition, because new objects are constantly replacing old objects, it is likely that some of the 30 to 40% of objects which are likely to be requested more than once are being overwritten by the objects which will never be requested again. It is therefore clear that the typical caching engine is working nowhere near the level of efficiency which is at least theoretically possible.
Techniques for improving caching efficiency are described in commonly assigned copending U.S. patent application Ser. No. 09/259,149 for METHODS AND APPARATUS FOR CACHING NETWORK TRAFFIC filed on Feb. 26, 1999, the entirety of which is incorporated herein by reference for all purposes. The invention described therein achieves improvements in caching efficiency by favoring the caching of objects which are statistically likely to be requested again. According to a one embodiment, when a caching engine experiences an initial cache miss for a requested object, the object is retrieved and sent to the requesting host but the object is not cached. Instead, the caching engine makes an entry corresponding to the requested object in a table in which it tracks objects for which at least one cache miss has occurred. If another request for the object is received, the object is retrieved, sent to the requesting host, and, because an entry corresponding to the requested object exists in the table, the object is cached. In other words, an object is only cached if it has been requested at least twice. The idea is that if an object has been requested two or more times it is statistically more likely to be requested again than an object for which only one request has been received. It follows then that, because the cache is populated only by objects which are likely to be requested, cache efficiency is correspondingly improved.
As it turns out, the frequency with which objects are requested on the web over a given relatively short period of time, e.g., two weeks, follows a distribution much like the well known Zipf distribution which represents the frequency of word usage in language. In such a distribution, a very small number of words (or objects in the network context) are used (or requested) at a frequency much greater than the majority of words (or objects). Therefore, it is desirable that caching systems take advantage of this relationship. That is, it would be advantageous to provide a caching system in which more frequently requested objects remain in the cache longer than less frequently requested objects.
Such a cache system should attempt to make the best use of its storage space to maximize the number of accesses to currently cached objects. One approach to this problem is represented by a least-recently-used LRU memory. A standard LRU queue operates according to a least recently used algorithm in which each time an object in the queue is accessed, it is moved to the head of the queue. When a new object is cached it is placed at the head of the queue and the item(s) at the end of the queue, i.e., the least recently used object(s), is (are) bumped from the queue.
Another approach is the use of a least-frequently-used (LFU) memory. This approach keeps track of the number of accesses for each object currently in the queue. The least frequently used object(s) in the queue is (are) bumped from the queue for the caching of a new object.
However, neither of these techniques takes advantage of the Zipf-like distribution followed by object requests in that any newly requested cacheable object is, at least initially, given the same status as any of the other objects in the queue. In addition, standard LRU memories have been shown to be effective only where the size of the cache is extremely large, quickly losing their abilities to hold valuable objects as the size of the content store is reduced. And LFU memories, while better than LRU memories for small to medium content stores, are computationally expensive.
Therefore, despite the improvements represented by all of the techniques described above, and given the value of any improvement in the usage of network transmission resources, it is desirable to improve the efficiency with which network caching systems cache data objects.